Comparison
gpt-neox vs litgpt
Verdict
Pick gpt-neox if gPT-NeoX from EleutherAI leverages GPU-based model parallelism via Megatron and DeepSpeed libraries to facilitate the training of large-scale autoregressive transformers in Python, under an Apache-2.0 license; pick litgpt if litGPT offers extensive support for high-performance LLMs with comprehensive workflows for pretraining, fine-tuning, and deployment.
Markdown twin · gpt-neox alternatives · litgpt alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | gpt-neox | litgpt |
|---|---|---|
| Maintenance | Steady (56d since push) As of 2w · github_public_v1 | Active (17d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- gpt-neox
- Implementation of model parallel autoregressive transformers on GPUs based on Megatron and DeepSpeed libraries
- litgpt
- High-performance LLMs with recipes for pretraining, finetuning and deployment
Stars
- gpt-neox
- 7.5k
- litgpt
- 14k
Forks
- gpt-neox
- 1.1k
- litgpt
- 1.5k
Open issues
- gpt-neox
- 111
- litgpt
- 272
Language
- gpt-neox
- Python
- litgpt
- Python
Adopt for
- gpt-neox
- GPT-NeoX from EleutherAI leverages GPU-based model parallelism via Megatron and DeepSpeed libraries to facilitate the training of large-scale autoregressive transformers in Python, under an Apache-2.0 license.
- litgpt
- LitGPT offers extensive support for high-performance LLMs with comprehensive workflows for pretraining, fine-tuning, and deployment.
Persona
- gpt-neox
- -
- litgpt
- -
Runtime
- gpt-neox
- -
- litgpt
- -
License
- gpt-neox
- The tool is licensed under Apache-2.0, allowing permissive use but emphasizing that derivative works must preserve copyright headers and licenses as per their origins
- litgpt
- LitGPT operates under the open-source Apache-2.0 license, providing permissive terms for use and modification.
Last pushed
- gpt-neox
- Jun 11, 2026
- litgpt
- Jul 20, 2026
Categories
- gpt-neox
- LLM Frameworks, Model Training
- litgpt
- Inference & Serving, LLM Frameworks, Model Training
Trust and health
Maintenance
- gpt-neox
- Steady (60%)
- litgpt
- Active (82%)
Days since push
- gpt-neox
- 56d
- litgpt
- 17d
Open issues (now)
- gpt-neox
- 111
- litgpt
- 272
Stars delta
- gpt-neox
- Unknown
- litgpt
- +137 (30d)
Open issues delta
- gpt-neox
- Unknown
- litgpt
- +6 (30d)
Full report
- gpt-neox
- Trust report
- litgpt
- Trust report
Choose gpt-neox if…
- Pricing: Free to use with the caveat of adhering to the Apache License terms, particularly in preserving copyright and license headers for all derivations..
- Tags unique to gpt-neox: deepspeed-library, gpt-3, language-model, transformers.
- - When your project requires a framework based on state-of-the-art libraries like Megatron and DeepSpeed that are optimized for large GPU clusters.
When NOT to use gpt-neox
- - In scenarios where minimal hardware resources, such as a single low-memory GPU or CPU-only environments, are available for training due to GPT-NeoX's requirement for a large-scale infrastructure.
- - If your project is limited by the Apache License terms or requires proprietary codebases without open-source contributions and modifications from external parties.
Choose litgpt if…
- Pricing: The core LitGPT framework is free to use under an open source license, but users might encounter costs when deploying at scale or using high-performance models..
- Requirements: Min 16 GB RAM.
- Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large language models.
- Also covers Inference & Serving.
- If you are focusing on a project that requires rapid prototyping or experimentation with over 20 different LLMs to find the best fit for your application.
When NOT to use litgpt
- If you need a tool specifically optimized for resource-constrained devices, as LitGPT focuses on high-performance LLMs and may require more resources.
- When your project is strictly limited to only one or two types of specific LLMs; in this case, another specialized framework that caters narrowly might be preferable.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (EleutherAI/gpt-neox) · observed Aug 7, 2026
- GitHub forks (EleutherAI/gpt-neox) · observed Aug 7, 2026
- Last push (EleutherAI/gpt-neox) · observed Jun 11, 2026
- License file (Apache-2.0) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Lightning-AI/litgpt) · observed Aug 7, 2026
- GitHub forks (Lightning-AI/litgpt) · observed Aug 7, 2026
- Last push (Lightning-AI/litgpt) · observed Jul 20, 2026
- License file (Apache-2.0) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: gpt-neox 7.5k · litgpt 14k (synced Aug 7, 2026).
Common questions
- What is the difference between gpt-neox and litgpt?
- gpt-neox: Implementation of model parallel autoregressive transformers on GPUs based on Megatron and DeepSpeed libraries. litgpt: High-performance LLMs with recipes for pretraining, finetuning and deployment. See the comparison table for live GitHub stats and shared categories.
- When should I choose gpt-neox over litgpt?
- Choose gpt-neox over litgpt when Pricing: Free to use with the caveat of adhering to the Apache License terms, particularly in preserving copyright and license headers for all derivations.; Tags unique to gpt-neox: deepspeed-library, gpt-3, language-model, transformers; - When your project requires a framework based on state-of-the-art libraries like Megatron and DeepSpeed that are optimized for large GPU clusters.
- When should I choose litgpt over gpt-neox?
- Choose litgpt over gpt-neox when Pricing: The core LitGPT framework is free to use under an open source license, but users might encounter costs when deploying at scale or using high-performance models.; Requirements: Min 16 GB RAM; Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large language models; Also covers Inference & Serving; If you are focusing on a project that requires rapid prototyping or experimentation with over 20 different LLMs to find the best fit for your application.
- When should I avoid gpt-neox?
- - In scenarios where minimal hardware resources, such as a single low-memory GPU or CPU-only environments, are available for training due to GPT-NeoX's requirement for a large-scale infrastructure. - If your project is limited by the Apache License terms or requires proprietary codebases without open-source contributions and modifications from external parties.
- When should I avoid litgpt?
- If you need a tool specifically optimized for resource-constrained devices, as LitGPT focuses on high-performance LLMs and may require more resources. When your project is strictly limited to only one or two types of specific LLMs; in this case, another specialized framework that caters narrowly might be preferable.
- Is gpt-neox or litgpt more popular on GitHub?
- litgpt has more GitHub stars (13,605 vs 7,452). Stars measure visibility, not whether either tool fits your constraints.
- Are gpt-neox and litgpt open source?
- Yes - both are open-source projects on GitHub (gpt-neox: Apache-2.0, litgpt: Apache-2.0).
- Where can I find alternatives to gpt-neox or litgpt?
- GraphCanon lists graph-backed alternatives at gpt-neox alternatives and litgpt alternatives (gpt-neox markdown twin, litgpt markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, gpt-neox or litgpt?
- gpt-neox: Steady. litgpt: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for gpt-neox and litgpt?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: gpt-neox trust report; litgpt trust report.